Collin Tokheim (@ctokheim) header
Collin Tokheim (@ctokheim) profile picture

Collin Tokheim

@ctokheim

Topics: Cancer Genomics; Data Science; Targeted Protein Degradation. Prev: @DamonRunyon Fellow, @DanaFarber / Harvard; PhD @JHUBME. Opinions=own.

 Boston, MA
github.com/ctokheim
Joined April 2018
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Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)Photo by Collin Tokheim (@ctokheim)
While AlphaGenome's non-coding variant interpretation is the major selling point, several aspects surrounding their protein-coding variant interpretation results gives the impression that they could be gaming benchmarks to inflate hype. 1/🧵
Anshul Kundaje (@anshulkundaje) profile pictureAnshul Kundaje@anshulkundajeSep 17
AlphaGenome (AG) & the AVI score is NOT "AI slop taking over genomics". I will give some concrete reasons why rather than evidence-free ranting (which I also like doing occasionally 😜). 1/
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If I am analyzing whole-exome sequencing (WES), it would not be unusual to have 1:100 or 1:1000 ratio. When I've benchmarked AlphaMissense in the past for identifying oncogenic mutations in cancer WES, this makes the PR-AUC values close to zero, instead of impressive looking 0.9
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So while I have no issue with AlphaGenome creating a precomputed AVI score to make the results more accessible, much like every other variant effect predictor. The utility though depends on how truly generalizable the results are.
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Mikko Taipale (@mike_tilapia) profile picture
Mikko Taipale@mike_tilapia20 Mar 2024
Our paper on functional discovery of protein degradation and stabilization effectors with proteome-scale induced proximity screens is out in its final version! 1/ nature.com/articles/s41586-0… rdcu.be/dBUju
Proteome-scale discovery of protein degradation and stabilization effectors

Proteome-scale discovery of protein degradation and stabilization effectors

Nature - A synthetic proteome-scale strategy enables the identification of a diverse range of human proteins that can induce the degradation or stabilization of a target protein in a...

nature.com
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Mikołaj Słabicki (@biomiko) profile picture
Mikołaj Słabicki@biomiko20 Mar 2023
Exciting news! Our DFCI-TPD webinar channel reached 100,000 views on YouTube! Huge thanks to all speakers who shared their expertise, and all viewers! None of this would have been possible without our exceptional team @kdonovan1008 @RPNowak @BLZerf6 @hojong_yoon @MilkaKostic
Image from Mikołaj Słabicki (@biomiko)
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Sharon Plon (@splon) profile picture
Sharon Plon@splon15 Mar 2023
In a packed room #ACMGMtg23 with @HeidiRehm Les Biesecker and Steve Harrison presenting the next version of variant classification work at @TheACMG @ClinGenResource AMP and CAP. Version 4 will be points based. All slides available at tinyurl.com/ACMG23
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Our lab website is online @MDAndersonNews ! mdanderson.org/research/depa… We're seeking highly motivated students, postdocs, and research assistants pursuing a career in cancer immunology and/or computational biology. Don't hesitate to apply!
Gu Laboratory

Gu Laboratory

The Gu lab is interested in enhancing the efficacy of cancer therapies, especially immunotherapy, by modulating cell-cell interactions.

mdanderson.org
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ML marches toward TPD. Degradability correlates with ubiquitination potential & E2-accessible lysines in this model. It‘s fairly well appreciated now that formation of a ternary complex is necessary but not sufficient. sciencedirect.com/science/ar…
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1/ My new book 'From Cell line to Command line' is finally here divingintogeneticsandgenomic… Grab it to start transforming yourself to a computational biologist! A thread on how this book came into being: 👇🧵
Image from Ming "Tommy" Tang (@tangming2005)
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Wubing Zhang (@Wubing44589261) profile picture
Wubing Zhang@Wubing445892617 Dec 2022
So happy to see publishing of my doctoral work on targeted protein degradation. I’m very grateful to my advisor @XShirleyLiu for being the best mentor. Thank @ctokheim for all mentoring and help. Also thank @ssroyburman and @kdonovan1008 @eric_fischer lab and all coauthors!
Xiaole Shirley Liu (@XShirleyLiu) profile pictureXiaole Shirley Liu@XShirleyLiu7 Dec 2022
sciencedirect.com/science/ar… This is our last piece of work on #proteindegradation at @dfcidatascience . Congratulations to @Wubing44589261 and @ctokheim , and thanks @eric_fischer Lab for the collaboration!
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